A new model for probabilistic multi-period multi-objective project selection problem

KHALILI-DAMGHANI, K., POORTARIGH, M. and PAKGOHAR, Alireza (2017). A new model for probabilistic multi-period multi-objective project selection problem. 24th International Conference on Production Research (ICPR 2017), 598-603.

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    Abstract

    The project selection problem is considered as one of the most imperative decisions for investor organizations. Due to non-deterministic nature of some criteria in the real world projects in this paper, a new model for project selection problem is proposed in which some parameters are assumed probabilistic. This model is formulated as a non-linear, multi-objective, multi-period, zero-one programming model. Then the epsilon constraint method and an algorithm are applied to check the Pareto front and to find optimal solutions. A case study is conducted to illustrate the applicability and effectiveness of the approach, with the results presented and analysed. Since the proposed model is more compatible with real world problems, the results are more tangible and trustable compared with deterministic cases. Implications of the proposed approach are discussed and suggestions for further work are outlined.

    Item Type: Article
    Additional Information: This article appeared in its original form in 24th International Conference on Production Research (2017). Lancaster, PA: DEStech Publications, Inc
    Uncontrolled Keywords: Project selection; multi objective programming; chance constraint; epsilon constraint method
    Page Range: 598-603
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 05 Mar 2019 13:16
    Last Modified: 12 Mar 2019 09:30
    URI: http://shura.shu.ac.uk/id/eprint/22728

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